Peptide charge state determination for low-resolution tandem mass spectra
Aaron Klammer, Christine C. Wu, Michael J. MacCoss and William Stafford
Proceedings of the Computational Systems Bioinformatics
Mass spectrometry is a particularly useful technology
for the rapid and robust identification of peptides and proteins in
complex mixtures. Peptide sequences can be identified by
correlating their observed tandem mass spectra (MS/MS) with theoretical
spectra of peptides from a sequence database. Unfortunately,
to perform this search the charge of the peptide must be known, and
current charge-state-determination algorithms only discriminate singly-
from multiply-charged spectra: distinguishing +2 from +3, for example,
is unreliable. Thus, search software is forced to
search multiply-charged spectra multiple times.
To minimize this inefficiency, we present a support vector machine
(SVM) that quickly and reliably classifies multiply-charged spectra as
having either a +2 or +3 precursor peptide ion. By classifying
multiply-charged spectra, we obtain a 40% reduction in search time
while maintaining an average of 99% of peptide and 99% of protein
identifications originally obtained from these spectra.
Charge Czar is a software tool for the classification of
multiply-charged low-resolution tandem mass spectra into either a +2
or +3 charge state. It consists of a single program:
Charge Czar is written in Python and ANSI C. Source code for the
latest version, as well as some pre-compiled versions for popular
platforms (Linux, Cygwin) can be
downloaded here. Charge Czar
is distributed under an open
Here are some
installation instructions and
release notes. The data used to train
Charge Czar can be found in a directory here and
as a zipped tar file here.
Charge Czar was written by Aaron Klammer in the Department of Genome Sciences at the University of Washington. The paper describing the method used by Charge Czar is available here, and should be cited as:
A. A. Klammer, C. C. Wu, M. J. MacCoss and W. S. Noble. Peptide charge
state determination for low-resolution tandem mass spectra. Proceedings
of the 2005 Computational Systems Bioinformatics Conference.
Aug 8-12, 2005: 175-185.